Alignments for a candidate for argB in Desulfovibrio vulgaris Hildenborough

GapMind for Amino acid biosynthesis

Alignments for a candidate for argB in Desulfovibrio vulgaris Hildenborough

Align acetylglutamate kinase (EC 2.7.2.8) (characterized)
to candidate 206911 DVU1466 acetylglutamate kinase

Query= BRENDA::Q9HTN2
         (301 letters)



>MicrobesOnline__882:206911
          Length = 308

 Score =  332 bits (850), Expect = 9e-96
 Identities = 167/294 (56%), Positives = 226/294 (76%), Gaps = 2/294 (0%)

Query: 6   DDAAQVAKVLSEALPYIRRFVGKTLVIKYGGNAMESEELKAGFARDVVLMKAVGINPVVV 65
           ++A   +KVL E+LPY+R+F G+T+VIKYGG+AM+ E LK  FA +V L+K VGINPV+V
Sbjct: 5   ENARLQSKVLIESLPYLRQFHGETVVIKYGGHAMKDEALKKAFALNVALLKLVGINPVIV 64

Query: 66  HGGGPQIGDLLKRLSIESHFIDGMRVTDAATMDVVEMVLGGQVNKDIVNLINRHGGSAIG 125
           HGGGPQIG +L++L+I+SHF +G+RVTD ATMDVVEMVL G+VNK+IVN +N  G  A+G
Sbjct: 65  HGGGPQIGKMLEQLNIQSHFREGLRVTDDATMDVVEMVLVGKVNKEIVNQMNLAGAKAVG 124

Query: 126 LTGKDAELIRAKKLTVTRQTPEMTKPEIIDIGHVGEVTGVNVGLLNMLVKGDFIPVIAPI 185
           L+GKD  LIRA+K+ +   + E   PEIID+G VGEV GVN  LL  L +  F+PVIAP+
Sbjct: 125 LSGKDGMLIRARKMEMV-ISKEAQAPEIIDLGKVGEVMGVNTTLLRSLERDGFVPVIAPV 183

Query: 186 GVGSNGESYNINADLVAGKVAEALKAEKLMLLTNIAGLMDKQGQVLTGLSTEQVNELIAD 245
           GV  NGE+YNINAD VAG VA ALKA++L+LLT++AG++D   +++  ++  +   L +D
Sbjct: 184 GVDDNGETYNINADAVAGAVAAALKAKRLLLLTDVAGILDHDKKLIRSVNMREAVNLFSD 243

Query: 246 GTIYGGMLPKIRCALEAVQGGVTSAHIIDGRVPNAVLLEIFTDSGVGT-LISNR 298
           GT+ GGM+PK++C LEA++ GV  A IIDGR  N +LLE+ TD GVGT ++S+R
Sbjct: 244 GTLTGGMIPKVKCCLEALEEGVEKAMIIDGRTENCILLELLTDKGVGTEIVSDR 297


Lambda     K      H
   0.318    0.138    0.381 

Gapped
Lambda     K      H
   0.267   0.0410    0.140 


Matrix: BLOSUM62
Gap Penalties: Existence: 11, Extension: 1
Number of Sequences: 1
Number of Hits to DB: 304
Number of extensions: 9
Number of successful extensions: 2
Number of sequences better than 1.0e-02: 1
Number of HSP's gapped: 1
Number of HSP's successfully gapped: 1
Length of query: 301
Length of database: 308
Length adjustment: 27
Effective length of query: 274
Effective length of database: 281
Effective search space:    76994
Effective search space used:    76994
Neighboring words threshold: 11
Window for multiple hits: 40
X1: 16 ( 7.3 bits)
X2: 38 (14.6 bits)
X3: 64 (24.7 bits)
S1: 41 (21.7 bits)
S2: 48 (23.1 bits)

Align candidate 206911 DVU1466 (acetylglutamate kinase)
to HMM TIGR00761 (argB: acetylglutamate kinase (EC 2.7.2.8))

# hmmsearch :: search profile(s) against a sequence database
# HMMER 3.3.1 (Jul 2020); http://hmmer.org/
# Copyright (C) 2020 Howard Hughes Medical Institute.
# Freely distributed under the BSD open source license.
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# query HMM file:                  ../tmp/path.aa/TIGR00761.hmm
# target sequence database:        /tmp/gapView.6316.genome.faa
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Query:       TIGR00761  [M=231]
Accession:   TIGR00761
Description: argB: acetylglutamate kinase
Scores for complete sequences (score includes all domains):
   --- full sequence ---   --- best 1 domain ---    -#dom-
    E-value  score  bias    E-value  score  bias    exp  N  Sequence                       Description
    ------- ------ -----    ------- ------ -----   ---- --  --------                       -----------
      5e-82  260.9   8.8    5.9e-82  260.7   8.8    1.0  1  lcl|MicrobesOnline__882:206911  DVU1466 acetylglutamate kinase


Domain annotation for each sequence (and alignments):
>> lcl|MicrobesOnline__882:206911  DVU1466 acetylglutamate kinase
   #    score  bias  c-Evalue  i-Evalue hmmfrom  hmm to    alifrom  ali to    envfrom  env to     acc
 ---   ------ ----- --------- --------- ------- -------    ------- -------    ------- -------    ----
   1 !  260.7   8.8   5.9e-82   5.9e-82       1     231 []      28     270 ..      28     270 .. 0.97

  Alignments for each domain:
  == domain 1  score: 260.7 bits;  conditional E-value: 5.9e-82
                       TIGR00761   1 tiViKiGGaais..elleelakdiaklrkegiklvivHGGgpeinelleklgievefvnglRvTdketlevvemvligk 77 
                                     t+ViK+GG+a++   l++++a ++a l+ +gi++vivHGGgp+i ++le+l+i+ +f +glRvTd +t++vvemvl+gk
  lcl|MicrobesOnline__882:206911  28 TVVIKYGGHAMKdeALKKAFALNVALLKLVGINPVIVHGGGPQIGKMLEQLNIQSHFREGLRVTDDATMDVVEMVLVGK 106
                                     69**********97899999*********************************************************** PP

                       TIGR00761  78 vnkelvallekhgikavGltgkDgqlltaekldke...........dlgyvGeikkvnkelleallkagiipviaslal 145
                                     vnke+v++++ +g+kavGl+gkDg l+ a+k++             dlg vGe+  vn+ ll++l   g++pvia++++
  lcl|MicrobesOnline__882:206911 107 VNKEIVNQMNLAGAKAVGLSGKDGMLIRARKMEMViskeaqapeiiDLGKVGEVMGVNTTLLRSLERDGFVPVIAPVGV 185
                                     ******************************66555556699************************************** PP

                       TIGR00761 146 deegqllNvnaDtaAaelAaaleAekLvlLtdvaGilegdkksliseleleeieqlikqavikgGmipKveaaleales 224
                                     d++g+++N+naD +A+++Aaal+A++L+lLtdvaGil++dkk li++++++e+ +l + + ++gGmipKv+++leale+
  lcl|MicrobesOnline__882:206911 186 DDNGETYNINADAVAGAVAAALKAKRLLLLTDVAGILDHDKK-LIRSVNMREAVNLFSDGTLTGGMIPKVKCCLEALEE 263
                                     ***************************************777.************************************ PP

                       TIGR00761 225 gvkkvvi 231
                                     gv+k++i
  lcl|MicrobesOnline__882:206911 264 GVEKAMI 270
                                     *****98 PP



Internal pipeline statistics summary:
-------------------------------------
Query model(s):                            1  (231 nodes)
Target sequences:                          1  (308 residues searched)
Passed MSV filter:                         1  (1); expected 0.0 (0.02)
Passed bias filter:                        1  (1); expected 0.0 (0.02)
Passed Vit filter:                         1  (1); expected 0.0 (0.001)
Passed Fwd filter:                         1  (1); expected 0.0 (1e-05)
Initial search space (Z):                  1  [actual number of targets]
Domain search space  (domZ):               1  [number of targets reported over threshold]
# CPU time: 0.01u 0.01s 00:00:00.02 Elapsed: 00:00:00.00
# Mc/sec: 7.21
//
[ok]

This GapMind analysis is from Apr 09 2024. The underlying query database was built on Apr 09 2024.

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About GapMind

Each pathway is defined by a set of rules based on individual steps or genes. Candidates for each step are identified by using ublast (a fast alternative to protein BLAST) against a database of manually-curated proteins (most of which are experimentally characterized) or by using HMMer with enzyme models (usually from TIGRFam). Ublast hits may be split across two different proteins.

A candidate for a step is "high confidence" if either:

ublast finds a hit to a characterized protein at above 40% identity and 80% coverage, and bits >= other bits+10.
- (Hits to curated proteins without experimental data as to their function are never considered high confidence.)
HMMer finds a hit with 80% coverage of the model, and either other identity < 40 or other coverage < 0.75.

where "other" refers to the best ublast hit to a sequence that is not annotated as performing this step (and is not "ignored").

Otherwise, a candidate is "medium confidence" if either:

ublast finds a hit at above 40% identity and 70% coverage (ignoring otherBits).
ublast finds a hit at above 30% identity and 80% coverage, and bits >= other bits.
HMMer finds a hit (regardless of coverage or other bits).

Other blast hits with at least 50% coverage are "low confidence."

Steps with no high- or medium-confidence candidates may be considered "gaps." For the typical bacterium that can make all 20 amino acids, there are 1-2 gaps in amino acid biosynthesis pathways. For diverse bacteria and archaea that can utilize a carbon source, there is a complete high-confidence catabolic pathway (including a transporter) just 38% of the time, and there is a complete medium-confidence pathway 63% of the time. Gaps may be due to:

our ignorance of proteins' functions,
omissions in the gene models,
frame-shift errors in the genome sequence, or
the organism lacks the pathway.

GapMind relies on the predicted proteins in the genome and does not search the six-frame translation. In most cases, you can search the six-frame translation by clicking on links to Curated BLAST for each step definition (in the per-step page).

For more information, see:

the paper from 2019 on GapMind for amino acid biosynthesis
the paper from 2022 on GapMind for carbon sources
the source code
instructions for running GapMind on your computer
changes to Amino acid biosynthesis since the publication.

If you notice any errors or omissions in the step descriptions, or any questionable results, please let us know

by Morgan Price, Arkin group, Lawrence Berkeley National Laboratory

GapMind for Amino acid biosynthesis